Position Overview:   
Insulet Corporation, maker of the OmniPod, is the leader in tubeless insulin pump. The Data Engineer role is responsible for data lake infrastructure, development of automated data uploads and scripting for data cleaning and analytics. Reporting to the Director Data Engineering, you will develop tools and processes to transform data for use by Insulet’s Analytics team, senior technical leaders and executives. We are a fast-growing company that provides an energetic work environment and tremendous career growth opportunities. 

Responsibilities:   

• Develop new and novel data architectures and pipelines and lead technical discussions to align stakeholders on the technical approach.   

• Design, develop, execute and document data validation strategies ensuring reliable data sources to drive enterprise decision making. 

• Develop and execute manual and automated test cases of data pipelines, ETL processes, and data transformations. 

• Work with cross-functional stakeholders to ensure quality and prompt delivery of data products. 

• Design, implementation and maintenance of Insulet’s data lake, warehouse and overall architecture  

• Create and maintain documentation of test plans, test cases and testing results. 

• Collaborate with data engineering and data teams to implement data quality best practices and optimize data workflows.  

• Design, monitor and maintain QA reports, KPIs & quality trends for the internal data engineering systems.  

• Interface with business stakeholders in cross-functional teams, including manufacturing, quality assurance, commercial, and post-market surveillance to understand various applications and their data sets. 

• Develop data validations tools as needed 

• Document data quality issues, testing procedures, and resolutions for future reference and knowledge sharing. 

Education and Experience:  

• Bachelors degree in Mathematics, Computer Science, Electrical or Computer Engineering, or a closely related STEM field is required with 5+ year’s experience 

• Master’s degree in Mathematics, Computer Science, Electrical and Computer Engineering, or a closely related STEM field;  

• Experience working with data technologies as Data Lake, Data Lakehouse, Data Warehouse 

• Experience in data quality assurance, control and lineage for large datasets in relational/non-relational databases  

• Experience managing robust ETL/ELT pipelines for big real-world datasets that could include messy data, unpredictable schema changes and/or incorrect data types  

• Experience with both batch data processing and streaming data  

• Experience validating deployments in different environments and executing tests 

• Experience in medical device, healthcare, or manufacturing industries is desirable  

• HIPAA experience a plus 

Skills/Competencies:   

• Demonstrated leadership at the time of validations and extreme focus on quality. 

• Demonstrated knowledge using IaC tools as Terraform and Cloud Formation 

• Demonstrated knowledge in SQL/relational and noSQL databases is required  

• Demonstrated knowledge of managing large data sets in the cloud (Data Lakes and Data Warehouses using AWS, GCP or Azure) is required  

• Knowledge of ETL and workflow tools (Azure Data Factory, AWS Glue, etc) is a plus  

• Demonstrated knowledge of deploying and maintaining and scaling cloud architectures (Azure, AWS, etc), specifically data tools that leverage Spark, is required  

• Demonstrated coding abilities in Python, Java, Scala or scripting languages  

• Demonstrated familiarity with different data types as inputs (e.g. CSV, XML, JSON, etc)  

• Demonstrated knowledge of database and dataset validation best practices  

• Ability to communicate effectively and document objectives and procedures